This document discusses the implementation of volume discount/price regimes using Microsoft Excel, focusing on deterministic demand processes with both uncapacitated and capacitated supply systems. It presents mathematical models and formulas to optimize revenue based on varying demand levels, alongside Excel implementation steps and illustrative examples. Additionally, it addresses the feasibility of achieving specified revenue targets using goal-seeking procedures.

1. International Journal of Mathematics and Statistics Invention (IJMSI)
E-ISSN: 2321 – 4767 P-ISSN: 2321 - 4759
www.ijmsi.org Volume 2 Issue 6|| June. 2014 || PP-01-08
www.ijmsi.org 1 | P a g e
Volume Discount/Price Regime Implementation on Microsoft
Excel Platform
Ukwu Chukwunenye
Department of Mathematics, University of Jos, P.M.B 2084 Jos, Nigeria.
ABSTRACT : Models were developed for volume discounts / price regime deterministic demand processes,
incorporating uncapacitated and capacitated supply systems. Then, the solutions were implemented on
Microsoft Excel platform by skillfully exploiting the composition of the minimum and maximum values concepts.
Finally, the Goal Seek procedure was exposed to determine demand levels that would achieve specified revenue
targets, with a note on the vexed issue of feasibility.
KEYWORDS: Code, Demand, Excel, Feasibility, Price, Revenue
I. INTRODUCTION
Consider a class of inventory problems in which the unit price is variable and depends on the quantity
to be purchased. Interest is usually focused on the revenue to be earned at given demand levels, how often
purchases are to be made and how many units should be ordered during any ordering period. Winston [1]
determined the economic order quantity (EOQ) for various time breaks without shortages and with backlogging
respectively; Hillier and Lieberman [2] determined the first economic lot-size model; Taha[3] considered the
case of EOQ with two price breaks; Verma[4] determined the optimal ordering policy for a four price-break
model; Gupta and Hira[5] examined two inventory model instances with three and four price break conditions in
which there are no optimal ordering policies corresponding to certain price breaks due to the infeasibility of the
Economic order quantities. Unfortunately thus far, there is no unifying single generic formula for the revenue
function and its implementation needed for the economic order quantity (EOQ). This article fills this yawning
gap.
II. PRELIMINARIES
We investigate the revenue accruable in the problem of a vendor offering price breaks based on
quantities demanded of a particular product for various demand and ordering policy contingencies. For
definiteness, let the demand process with thecorresponding price regime in arbitrary monetary units be as
tabulated below:
Given product Unit price
First q1 units
Next q2 units
Next q3 units
…
Next qk-1 units
Next further units
p1
p2
p3
…
pk-1
Pk
Table 1:Price Breaks
Two cases are examined.
Case 1: Determine the revenue accruing to the vendor when actual demand level is v and the supply capacity is
unconstrained,
Case 2: Determine the revenue when actual demand level is v and the supply capacity is constrained.
A note on case 1: The feasibility of case 1 is established if backlogging of demand is allowed, when supply is
exceeded. The main results of this paper are collected into the five sections3 through7. Section 3 deals with the
formulation and derivation of the revenue formula for specified demand levels with respect to uncapacitated and
capacitated supplies.Section 4 is concerned with the translation of above revenue formula into appropriate
mathematical format needed for the implementation of the revenue formulas on Microsoft Excel
platform.Section 5provides and implements the codeforthe revenue formula of section 4on Excel platform.
Section 6 furnishes illustrative examples of above supply cases. Finally, in section 7, the Goal Seek procedure

2. Volume Discount/Price Regime Implementation…
www.ijmsi.org 2 | P a g e
is used to determine demand levels that yield specified revenue targets. The results obtained in this procedure
are optimal if they are nonnegative and discrete, or infeasible otherwise, in which case a satisficing solution
obtained by rounding up or down the nearest integer may be considered, depending on the financial sensitivity
of the given problem.
III. RESULTS AND DISCUSSIONS
3.1. Theorem on Revenue arising from case 1: unconstrained availability
Denote the revenue from v units by ( ).R v Then ( )R v is given by:
1 1
1 1 2 1) 1 1 2
1 1 2 2 3 1 2 1 2 1 2 3
2 2 2 1
1
1 1 1 1
1 1
1 1
, if 0 (1)
( if (2)
( ( ) ) if (3)
( )
if ( 1)
if
k k k k
j j k j j j j
j j j j
k k
j j k j
j j
p v v q
p q p v q q v q q
p q p q p v q q q q v q q q
R v
p q p v p q q v q k
p q p v q v
   

   
 
 
 
    
        

    
  
 
 
 
 
 
 
   
 

1
1
( )
k
j
j
q k
















Proof
Proof is by mathematical induction on v. If 0 1 v q , then the unit price 1p is applicable. The obtainable
revenue is the product of the number of units demanded and the unit price on offer. Thus, 1( ) ,R v p v for
0 1 v q . Assume that the relation is true for v such that q v qj
j
i
j
j
i



  
1
1
1
, for some 2  i k . Then
by the induction hypothesis, the revenue corresponding to v is p q p v qj j
j
i
i j
j
i




  






1
1
1
1
.
1
1 1 1
1 1
1 1
1
1
Suppose 2. If , then the demand is first satisfied, with
corresponding revenue . The revenue corresponding to the left-over
units is
i i i
j j j
j j j
i i
j j j j
j j
i
i j
j
i k q v q q
p q p q
p v q

  
 
 


   





  
 

1 1 1 1
1
1 1
. Hence the total revenue is + .
i i
j j i j
j j
p q p v q
   

 

  
  
  
 
1 1 1 1
1
1 1 1
Finally, if 1 and , then ( ) .
i i i
j j j i j
j j j
i k v q R v p q p v q
   

  
     
 
 
 
  
Therefore, the relation is true with respect to the index i +1. This proves the theorem.
3.2. Corollary on Revenue arising from case 2: constrained availability/supply
 
1
1
1
1
Denote the supply capacity by , et max . 0 , replace the expression
in equation ( ) of theorem 3.1 by . Replace by min , . Then
( ) in the formula theorem 3.1 modi
k
k j
j
k
k j k k
j
s s q s q
p v q k p q v s v
R v




 

 
 
 
 
 
 


  fies to min , . The proof is immediate from
table 1 and the proof of theorem 3.1.
R s v
The unsatisfied demand is given by max({ ,0});v s this demand may be backlogged bymutual agreement.

3. Volume Discount/Price Regime Implementation…
www.ijmsi.org 3 | P a g e
IV. FORMAT OF REVENUE FORMULAS FOR EXCEL IMPLEMENTATION
In this section, the formulas obtained in section 3 will be translated into appropriate formats for Excel
implementation, by manipulating the max / min concept. The utility / elegance of this translation can be
appreciated by the fact that ( )R v collapses to only one expression. Compare this with the horrendous looking
piece – wise expressions for ( )R v and (min{ , })R s v in section 3. The embedded price break conditions called
for a high degree of mathematical insight. Both cases will now be revisited.
Case 1
Suppose that v is the actual demand. Then v can be distributed among the price breaks 1 2, , , ,kp p p to
yield the following table:
Given product Unit price Demand
First q1 units
Next q2 units
Next q3 units
…
Next qk – 1 units
Further units
p1
p2
p3
…
pk– 1
pk
v 1
v2
v3
…
vk– 1
vk
Table 2. Price breaks with actual demands
1
1
where , 0; 0, for otherwise 0, a vacuous case.
k
j j
j
v v v v v

   
Above insight triggers the translation of R(v) into the format given bythe theorembelow
11 1
1 1 1
0
1
Theorem 4.1: For any demand level ,
( ) max min , , 0 max , 0 , 1,
where 0.
jk k
j i j k l
j i l
j
j
v
R v p v q q p v q k
f
 
  

    

    
     
   
  

Proof
For any finite demand level , the expression for the corresponding revenue, ( ) isv R v
1 1 2 1 2 3 1 2 3
1 1 2 2 1
( ) min{ , } max{min{ , }, 0} max{min{ ( ), }, 0}
max{min{{ ( ), }, 0}k k k
R v p v q p v q q p v q q q
p v q q q q  
     
      
1 2 2 1
1 1
max{ ( ), 0}.
Note that max{min{ , }} min{ , }.Therefore, ( ) can be expressed more succintlyand
compactly in the form stated in the theorem.
k k k
p v q q q q
v q v q R v
 
     


Case 2
Recall that the modifications on case 1, yielding case 2 assure that
 
1
1 1
1
1 1
(min{ , }) , where max , 0 .
Above expression translates to the relation:
(min{ , }) max min min , , , 0 , for any specified demand level .
k k
j j k j
j j
jk
j i j
j i
R s v p q q s q
R s v p s v q q v

 

 
  
 
 
 
 
  
   
  
 
 

4. Volume Discount/Price Regime Implementation…
www.ijmsi.org 4 | P a g e
V. IMPLEMENTATIONOF RESULTS
This section deals with mathematical implementation of the results of section four on the Microsoft
Excel platform and the Goal Seek procedure.
5.1 Mathematical Implementation of Results
Case 1: The data can be organized in an Excel worksheet as shown below:
A B C D
1 Volume Discounts Model Implementation
2
3 Incremental
volume for
price breaks
Case : Actual Demand = v
4 Unit price Incr_Rev.
5
6
7 q1 p1
8 q2 p2
9 q3 p 3
. . .
. . .
. . .
n – 1 qk-1 pk-1
n pk
n + 1
n +2 Actual Demand = v
n + 3 Supply cap. = infinity Total_Rev. =
Table 3:General Excel implementations of revenues
Let ( )j jR R v denote the incremental revenue (Incr_Rev.) corresponding to the price
break {1,2, , },;j j kp   for a given demand level .v
Implementation
Step 1: Type =$B7*max (min ($B$n+2-sum ($A$6:$A6), $A7), 0) in cell D7. <ENTER> to obtain the
revenue R1 corresponding to the demand min {v, q1}.
Step 2: Place the cursor on the right boundary of cell D7; it immediately changes to a crosshair. Drag
the crosshair down to cell Dn-1. <ENTER> to secure the incremental revenues corresponding to all price breaks
except the last price break.
Step 3: Type = $B$n*max ($C$n+2 – sum ($A7:$An-1), 0) in cell Dn.
1
1
<ENTER> to obtain the revenue for the demand max . 0 .
k
k j
j
q s q


 
 
 
 

corresponding to the last price break.
Step 4: Type = sum ($D7:$Dn) in cell Dn+2. <ENTER> to obtain the total revenue ( ).R v
Case 2
Step 1: Write “Supplycap.= ” in cell An+3. Suppose that the capacity is s. Type in the value of s in cell
Bn+3. Type the following in cell An+2:
= max (min ($B$n+2, $B$n+3) – sum ($A$7:$A$n-1), 0). <ENTER> to secure qk.
Step 2: Follow steps 1 and 2 of case 1 implementation with the crosshair dragging process extended to
cell Dn. <ENTER> to generate all incremental revenues.
Step 3: Use step 4 of case 1 implementation to obtain the total revenue (min{ , }).R s v
Note that the demand v – min{s, v} is unsatisfied.

5. Volume Discount/Price Regime Implementation…
www.ijmsi.org 5 | P a g e
VI. ILLUSTRATIVE EXAMPLES
Two examples of case1 are displayed below, illustrating the scenario v q j
j
k
 


1
1
1
1
and the scenario
k
j
j
v q


  . In the first scenario, note the placements of the zeros in the D column, reflecting
the fact that ( ) 0 for all 1,R v l j   whenever
1
1 1
, for some .i i
j j
i i
q v q j

 
  
Incremental
Volume for Case v = : 2000 3000
Price Breaks Unit Price Incr_rev Incr_rev
500 500 250000 250000
460 470 216200 216200
430 450 193500 193500
390 420 163800 163800
330 400 88000 132000
270 380 0 102600
220 360 0 79200
200 330 0 66000
170 310 0 52700
300 0 9000
Demand = 2000 Total_rev= 911,500.00 1,265,000.00
Supply cap =
Volume Discount Model Implementation
Table 4: Excel implementations of revenues for given data..
A B C D E
1 Volume Discounts Model Implementation
2
3 Incremental
Volume for
Price breaks
4 Case: v=2000 v=3000
5 Unit price Incr_rev Incr_rev
6
7 500 500 250000 250000
8 460 470 216200 216200
9 430 450 193500 193500
10 390 420 163800 163800
11 330 400 88000 132000
12 270 380 0 102600
13 220 360 0 79200
14 200 330 0 66000
15 170 310 0 52700
16 300 0 9000
17
18 Demand = 2000 Total_rev = 911,500 1,265,000
19 Supply cap =
Table 5:Full view of Excel implementations of revenues for given data in Table 4.

6. Volume Discount/Price Regime Implementation…
www.ijmsi.org 6 | P a g e
6.2 Unconstrained supply Implementation Example
Using the demand v = 3000, the outputs are as shown in column E, with Total revenue equal to 1,
265,000.
6.3 Constrained supply Implementation Example
Step 1: Type in 1500 in cell B19. This is the supply capacity. Type 2000 in cell B18 for the actual
demand. Type the following code in cell A16:
= max (min ($B$19, $B$18) – sum ($A$7:$A$15), 0). This is the value of q10. Here, k = 10.
Step 2: Type = $B7*max (min ($C$19, $C$18) – sum ($A$6:$A6), $A7), 0) in cell D7; <ENTER> to obtain
the revenue R1 corresponding to the demand min {min {v, s}, q1}.
Step 3: Place the cursor on the right boundary of cell D7 and drag the crosshair down to cell D16 to
secure 2
R through 10
R The results are 1
250,000,R  2 3
216,200, 193,500,R R 
4 5 6 10
46, 200, , 0. Total revenue 705,900.R R R R    
6.4 Constrained supply Example
Now use the values 3,200 and 3,500 for the demand and supply capacity to secure the outputs
1
250,000,R  2 3
216,200, 193,500,R R  4 5 6
163,800, 132,00, 102,600,RR R  
7 8 9 10
79,200, 66,000, 527,000, 69,000. Total revenue 1,325,000.R R R R    
VII. THE GOAL SEEK PROCEDURE
Goal Seek is a sensitivity analysis procedure. It adjusts a value in a specified cell until a dependent
formula achieves the desired goal. For example, Goal Seek can be used to find the sales figures needed for a
salesperson to achieve a desired total monthly wage based on a fixed commission rate, bonus qualification
requirement and its associated payment rate. To make this mathematically precise, suppose that the commission
rate is 1r % of the total sales figures 1x and the bonus rate is 2r , based
on a minimum sales figure 2.x Let 1 2 1 2f ( x ,x ,r ,r ) denote the total monthly wage of a
salesperson with above sales figure. Then
2 2 1 2
1 2 1 2 1 1
, if
( , , , )
0, otherwise
r x x x
y f x x r r r x

  



 1 2 1 2 1 1 2 2 1 2
or ( , , , ) sgn max{ ,0} , infinitesimally positive.y f x x r r r x r x x x      
Suppose that the cell references for the values x1,x2, r1%, r2%, and the total monthly wage are C10, C11, C12,
C13 and C14 respectively. Then this formula would be translated to the following Excel code in cell C14:
= $C12*$C10 + $C13*IF( $C10 >= $C11, $C10, 0 ). Pressing the ENTER key implements the code
with the output in cell C14. Subsequently, to get the sales figure corresponding to a desired monthly wage, you
would click on the target cell, C14 and then invoke the GOAL SEEK feature.
GOAL SEEK will now be applied first to the infinite supply capacity case.
Click on the target cell, E18. Invoke GOAL SEEK on the Tools menu:
Figure 1: Goal seek dialogue box

7. Volume Discount/Price Regime Implementation…
www.ijmsi.org 7 | P a g e
7.1 The Goal Seek Implementation Example: Uncapacitated Supply Case.
Changing the value of cell E18 under the Goal Seek: Type the desired target revenue, 900000 say, in
the To value text box. Type in the cell reference of the cell to be changed, C18 in the By changing cell text box.
Click OK to implement GOAL SEEK (Cancel to abort the procedure). The following dialog box appears.
Figure 2: Goal seek status box with target value
The Stop and Pause buttons are ghosted to indicate that those options are unavailable. Click Ok to
accept the result. Click Cancel to abort the GOAL SEEK activity. If Ok is clicked, the incremental revenues
change automatically to reflect the change in the total revenue and demand
The Goal Seek output demand and incremental revenues are 1971.25; 1
250,000,R  in cell D7,
2
216,200,R  in cell D8, 3
193,500,R  in cell D9, 4
163,800,R  in cell D10, 5
76,500,R 
in cell D11, 6 0,R  in cell D12, 7
0,R  in cell D13, 8
0,R  in cell D14,
9
0,R  in cell D15,and 10 0,R  in cell 16.
Unfortunately, the new demand generated by Goal Seek is non-integral. A satisficing demand can be
generated from
argmin {abs(R(1971) – 900,000), abs(R(1972) – 900,000). Type in 1971 and 1972 in cell C18,
followed by the execution of “<ENTER>” in each case, to obtain the revenues 899,900 and 900,300
respectively.
Clearly, argmin {abs(R (1971) – 900,000), abs(R (1972) – 900,000) = 1971. This new demand may be
accepted, depending on the financial sensitivity of the problem, as well as the company objectives.
7.2The Goal Seek Implementation Example: Capacitated Supply Case.
Apply the Goal Seek procedure to table with supply capacity = 3,500, demand = 3,200 and total revenue of
1,000,000.
VIII. RESULTS
R1 = 250,000, in cell D7, R2 = 216,200, in cell D8, R3 =193,500, in cell D9,
R4 = 163,800, in cell D10, R5 = 132,000, in cell D11, R6= 44,500, in cell D12, R7 = 0, in cell D13, R8 = 0, in
cell D14, R9 = 0, in cell D15,and R10 = 0, in cell 16.
Generated demand = 2,227.105. The reader should verify that
Argmin {abs(R(2,227) – 1,000,000), abs(R(2,228) – 1,000,000) = 2,227.
Observe even after the Goal Seek activity has been completed, the results could still be discarded and the
original results reverted to by the use of <CTRL_Z>; <CRTL_Y> reverts to the Goal Seek results.
IX. CONCLUSION
This paper, with its novel approach has been motivated by the need to expose the reader to the multi-
stage process of model development and implementation / automation, as applied to aspects of volume discount
problems.The insight gained from the unique and broad techniques of presentation and strategy of proofs can be
leveraged to solve related problems and may even be extended to appropriate model building
situations. Furthermore, most readers who do not have access to customized inventory software can readily
Goal Seeking with cell C18 :
Found a solution
Target value:900,000
Current value :900,000
By changing cell :
Goal Seek Status ? X
Pause
Ok
Stop
Cancel

8. Volume Discount/Price Regime Implementation…
www.ijmsi.org 8 | P a g e
exploit the established results to solve this class of problems on Excel platform, which is widely and readily
available.
REFERENCES
[1] Winston, L. W. Operations Research: Applications and Algorithms, Duxbury Press, Boston. (1994)pp. 692-697, 700-705.
[2 ] Hillier, F. S. and Lieberman, G. J.Introduction to Operations Research.Sixth Edition.McGraw-Hill, Inc., New York (1995).p.766.
[3] Taha, H. A. Operations Research: An Introduction. Seventh Edition.Prentice-Hall of India, New Delhi. (2006). pp. 435-438
[4] Verma, A. P. Operations Research. S. K. Kataria& Sons. New Delhi. (2010). pp. 843-847.
[5] Gupta, P. K. and Hira, D. S. Problems in Operations Research (Principles and Solutions). S. Chand & Company Ltd. New Delhi
(2012). pp. 917-921